{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d8f7363c",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4a937fbd",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams['font.sans-serif']=[u'SimHei']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5c76e236",
   "metadata": {},
   "outputs": [],
   "source": [
    "data=pd.read_excel(\"景区厕所推送信息/cata_5707_xls/cata_5707_1.xls\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a4ccd40c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>所在县</th>\n",
       "      <th>区划编码</th>\n",
       "      <th>项目编号</th>\n",
       "      <th>业主单位</th>\n",
       "      <th>管理类型</th>\n",
       "      <th>建设性质</th>\n",
       "      <th>省级审批完成时间</th>\n",
       "      <th>项目类别</th>\n",
       "      <th>实际开工日期</th>\n",
       "      <th>国家审批完成时间</th>\n",
       "      <th>...</th>\n",
       "      <th>男厕位</th>\n",
       "      <th>图片url地址</th>\n",
       "      <th>第三卫生间</th>\n",
       "      <th>完成情况</th>\n",
       "      <th>附件url地址</th>\n",
       "      <th>市级审批完成时间</th>\n",
       "      <th>计划申报时间</th>\n",
       "      <th>主键</th>\n",
       "      <th>名称</th>\n",
       "      <th>所在市</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>普陀区</td>\n",
       "      <td>330903</td>\n",
       "      <td>ZJ-ZS-0384</td>\n",
       "      <td>杉杉·普陀天地景区</td>\n",
       "      <td>自管</td>\n",
       "      <td>新建</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>旅游景区</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>无</td>\n",
       "      <td>0</td>\n",
       "      <td>已完工</td>\n",
       "      <td>无</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>ZJ-ZS-0384</td>\n",
       "      <td>C1二楼公厕</td>\n",
       "      <td>舟山市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>萧山区</td>\n",
       "      <td>330109</td>\n",
       "      <td>ZJ-HAZ-1570</td>\n",
       "      <td>浙旅院国际教育旅游体验区</td>\n",
       "      <td>自管</td>\n",
       "      <td>新建</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>旅游景区</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>无</td>\n",
       "      <td>0</td>\n",
       "      <td>已完工</td>\n",
       "      <td>无</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>ZJ-HAZ-1570</td>\n",
       "      <td>519剧院厕所3</td>\n",
       "      <td>杭州市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>萧山区</td>\n",
       "      <td>330109</td>\n",
       "      <td>ZJ-HAZ-1485</td>\n",
       "      <td>杭州市湘湖景区</td>\n",
       "      <td>自管</td>\n",
       "      <td>新建</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>旅游景区</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>无</td>\n",
       "      <td>1</td>\n",
       "      <td>已完工</td>\n",
       "      <td>无</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>ZJ-HAZ-1485</td>\n",
       "      <td>城山广场生态厕所</td>\n",
       "      <td>杭州市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>萧山区</td>\n",
       "      <td>330109</td>\n",
       "      <td>ZJ-HAZ-1584</td>\n",
       "      <td>浙旅院国际教育旅游体验区</td>\n",
       "      <td>自管</td>\n",
       "      <td>新建</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>旅游景区</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>无</td>\n",
       "      <td>0</td>\n",
       "      <td>已完工</td>\n",
       "      <td>无</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>ZJ-HAZ-1584</td>\n",
       "      <td>行政楼十四楼厕所</td>\n",
       "      <td>杭州市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>嵊州市</td>\n",
       "      <td>330683</td>\n",
       "      <td>ZJ-SX-0953</td>\n",
       "      <td>嵊州市瞻山风景旅游区</td>\n",
       "      <td>自管</td>\n",
       "      <td>新建</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>旅游景区</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>无</td>\n",
       "      <td>0</td>\n",
       "      <td>已完工</td>\n",
       "      <td>无</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>1900-01-01 00:00:00.0</td>\n",
       "      <td>ZJ-SX-0953</td>\n",
       "      <td>公共厕所</td>\n",
       "      <td>绍兴市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4995</th>\n",
       "      <td>龙游县</td>\n",
       "      <td>330825</td>\n",
       "      <td>ZJ-QZ-2679</td>\n",
       "      <td>横山镇后徐村</td>\n",
       "      <td>自管</td>\n",
       "      <td>改建</td>\n",
       "      <td>2018-12-05 00:00:00.0</td>\n",
       "      <td>乡村旅游点</td>\n",
       "      <td>2018-12-05 00:00:00.0</td>\n",
       "      <td>2018-12-05 00:00:00.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>无</td>\n",
       "      <td>0</td>\n",
       "      <td>已完工</td>\n",
       "      <td>无</td>\n",
       "      <td>2018-12-05 00:00:00.0</td>\n",
       "      <td>2018-12-05 00:00:00.0</td>\n",
       "      <td>ZJ-QZ-2679</td>\n",
       "      <td>横山镇后徐村桥头旅游公厕</td>\n",
       "      <td>衢州市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4996</th>\n",
       "      <td>南浔区</td>\n",
       "      <td>330503</td>\n",
       "      <td>ZJ-HUZ-1201</td>\n",
       "      <td>练市镇蔡家桥村</td>\n",
       "      <td>自管</td>\n",
       "      <td>新建</td>\n",
       "      <td>2018-05-05 00:00:00.0</td>\n",
       "      <td>其他</td>\n",
       "      <td>2019-05-19 00:00:00.0</td>\n",
       "      <td>2018-05-05 00:00:00.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>无</td>\n",
       "      <td>0</td>\n",
       "      <td>已完工</td>\n",
       "      <td>无</td>\n",
       "      <td>2018-05-05 00:00:00.0</td>\n",
       "      <td>2018-05-05 00:00:00.0</td>\n",
       "      <td>ZJ-HUZ-1201</td>\n",
       "      <td>蔡家桥公园旅游厕所</td>\n",
       "      <td>湖州市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4997</th>\n",
       "      <td>海宁市</td>\n",
       "      <td>330481</td>\n",
       "      <td>ZJ-JX-0876</td>\n",
       "      <td>五丰村</td>\n",
       "      <td>自管</td>\n",
       "      <td>改建</td>\n",
       "      <td>2019-06-30 00:00:00.0</td>\n",
       "      <td>乡村旅游点</td>\n",
       "      <td>2019-01-08 00:00:00.0</td>\n",
       "      <td>2019-06-30 00:00:00.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>无</td>\n",
       "      <td>1</td>\n",
       "      <td>已完工</td>\n",
       "      <td>无</td>\n",
       "      <td>2019-06-30 00:00:00.0</td>\n",
       "      <td>2019-06-30 00:00:00.0</td>\n",
       "      <td>ZJ-JX-0876</td>\n",
       "      <td>黄湾镇五丰村旅游厕所一号</td>\n",
       "      <td>嘉兴市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4998</th>\n",
       "      <td>龙游县</td>\n",
       "      <td>330825</td>\n",
       "      <td>ZJ-QZ-2654</td>\n",
       "      <td>詹家镇山后村</td>\n",
       "      <td>自管</td>\n",
       "      <td>新建</td>\n",
       "      <td>2018-11-08 00:00:00.0</td>\n",
       "      <td>乡村旅游点</td>\n",
       "      <td>2018-11-08 00:00:00.0</td>\n",
       "      <td>2018-11-08 00:00:00.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>无</td>\n",
       "      <td>1</td>\n",
       "      <td>已完工</td>\n",
       "      <td>无</td>\n",
       "      <td>2018-11-08 00:00:00.0</td>\n",
       "      <td>2018-11-08 00:00:00.0</td>\n",
       "      <td>ZJ-QZ-2654</td>\n",
       "      <td>詹家镇山后村旅游公厕</td>\n",
       "      <td>衢州市</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4999</th>\n",
       "      <td>龙游县</td>\n",
       "      <td>330825</td>\n",
       "      <td>ZJ-QZ-2644</td>\n",
       "      <td>龙洲街道山底村</td>\n",
       "      <td>自管</td>\n",
       "      <td>新建</td>\n",
       "      <td>2018-11-15 00:00:00.0</td>\n",
       "      <td>乡村旅游点</td>\n",
       "      <td>2018-12-11 00:00:00.0</td>\n",
       "      <td>2018-11-15 00:00:00.0</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>无</td>\n",
       "      <td>1</td>\n",
       "      <td>已完工</td>\n",
       "      <td>无</td>\n",
       "      <td>2018-11-15 00:00:00.0</td>\n",
       "      <td>2018-11-15 00:00:00.0</td>\n",
       "      <td>ZJ-QZ-2644</td>\n",
       "      <td>龙洲街道山底村旅游公厕</td>\n",
       "      <td>衢州市</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5000 rows × 40 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      所在县    区划编码         项目编号          业主单位 管理类型 建设性质               省级审批完成时间  \\\n",
       "0     普陀区  330903   ZJ-ZS-0384     杉杉·普陀天地景区   自管   新建  1900-01-01 00:00:00.0   \n",
       "1     萧山区  330109  ZJ-HAZ-1570  浙旅院国际教育旅游体验区   自管   新建  1900-01-01 00:00:00.0   \n",
       "2     萧山区  330109  ZJ-HAZ-1485       杭州市湘湖景区   自管   新建  1900-01-01 00:00:00.0   \n",
       "3     萧山区  330109  ZJ-HAZ-1584  浙旅院国际教育旅游体验区   自管   新建  1900-01-01 00:00:00.0   \n",
       "4     嵊州市  330683   ZJ-SX-0953    嵊州市瞻山风景旅游区   自管   新建  1900-01-01 00:00:00.0   \n",
       "...   ...     ...          ...           ...  ...  ...                    ...   \n",
       "4995  龙游县  330825   ZJ-QZ-2679        横山镇后徐村   自管   改建  2018-12-05 00:00:00.0   \n",
       "4996  南浔区  330503  ZJ-HUZ-1201       练市镇蔡家桥村   自管   新建  2018-05-05 00:00:00.0   \n",
       "4997  海宁市  330481   ZJ-JX-0876           五丰村   自管   改建  2019-06-30 00:00:00.0   \n",
       "4998  龙游县  330825   ZJ-QZ-2654        詹家镇山后村   自管   新建  2018-11-08 00:00:00.0   \n",
       "4999  龙游县  330825   ZJ-QZ-2644       龙洲街道山底村   自管   新建  2018-11-15 00:00:00.0   \n",
       "\n",
       "       项目类别                 实际开工日期               国家审批完成时间  ...  男厕位 图片url地址  \\\n",
       "0      旅游景区  1900-01-01 00:00:00.0  1900-01-01 00:00:00.0  ...    7       无   \n",
       "1      旅游景区  1900-01-01 00:00:00.0  1900-01-01 00:00:00.0  ...    6       无   \n",
       "2      旅游景区  1900-01-01 00:00:00.0  1900-01-01 00:00:00.0  ...    6       无   \n",
       "3      旅游景区  1900-01-01 00:00:00.0  1900-01-01 00:00:00.0  ...    8       无   \n",
       "4      旅游景区  1900-01-01 00:00:00.0  1900-01-01 00:00:00.0  ...    4       无   \n",
       "...     ...                    ...                    ...  ...  ...     ...   \n",
       "4995  乡村旅游点  2018-12-05 00:00:00.0  2018-12-05 00:00:00.0  ...    4       无   \n",
       "4996     其他  2019-05-19 00:00:00.0  2018-05-05 00:00:00.0  ...    4       无   \n",
       "4997  乡村旅游点  2019-01-08 00:00:00.0  2019-06-30 00:00:00.0  ...    4       无   \n",
       "4998  乡村旅游点  2018-11-08 00:00:00.0  2018-11-08 00:00:00.0  ...    6       无   \n",
       "4999  乡村旅游点  2018-12-11 00:00:00.0  2018-11-15 00:00:00.0  ...    8       无   \n",
       "\n",
       "     第三卫生间 完成情况  附件url地址               市级审批完成时间                 计划申报时间  \\\n",
       "0        0  已完工        无  1900-01-01 00:00:00.0  1900-01-01 00:00:00.0   \n",
       "1        0  已完工        无  1900-01-01 00:00:00.0  1900-01-01 00:00:00.0   \n",
       "2        1  已完工        无  1900-01-01 00:00:00.0  1900-01-01 00:00:00.0   \n",
       "3        0  已完工        无  1900-01-01 00:00:00.0  1900-01-01 00:00:00.0   \n",
       "4        0  已完工        无  1900-01-01 00:00:00.0  1900-01-01 00:00:00.0   \n",
       "...    ...  ...      ...                    ...                    ...   \n",
       "4995     0  已完工        无  2018-12-05 00:00:00.0  2018-12-05 00:00:00.0   \n",
       "4996     0  已完工        无  2018-05-05 00:00:00.0  2018-05-05 00:00:00.0   \n",
       "4997     1  已完工        无  2019-06-30 00:00:00.0  2019-06-30 00:00:00.0   \n",
       "4998     1  已完工        无  2018-11-08 00:00:00.0  2018-11-08 00:00:00.0   \n",
       "4999     1  已完工        无  2018-11-15 00:00:00.0  2018-11-15 00:00:00.0   \n",
       "\n",
       "               主键            名称  所在市  \n",
       "0      ZJ-ZS-0384        C1二楼公厕  舟山市  \n",
       "1     ZJ-HAZ-1570      519剧院厕所3  杭州市  \n",
       "2     ZJ-HAZ-1485      城山广场生态厕所  杭州市  \n",
       "3     ZJ-HAZ-1584      行政楼十四楼厕所  杭州市  \n",
       "4      ZJ-SX-0953          公共厕所  绍兴市  \n",
       "...           ...           ...  ...  \n",
       "4995   ZJ-QZ-2679  横山镇后徐村桥头旅游公厕  衢州市  \n",
       "4996  ZJ-HUZ-1201     蔡家桥公园旅游厕所  湖州市  \n",
       "4997   ZJ-JX-0876  黄湾镇五丰村旅游厕所一号  嘉兴市  \n",
       "4998   ZJ-QZ-2654    詹家镇山后村旅游公厕  衢州市  \n",
       "4999   ZJ-QZ-2644   龙洲街道山底村旅游公厕  衢州市  \n",
       "\n",
       "[5000 rows x 40 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7a059f7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x193fd1d5a48>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(data[\"所在市\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "79cc95df",
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'Series' object has no attribute 'pie'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-8-52b008f318f3>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m# https://blog.csdn.net/qq_41081716/article/details/103128866\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;31m# plt.plot(data[\"所在市\"])\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mdata\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"所在市\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpie\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32md:\\project\\python_project\\albert\\venv\\lib\\site-packages\\pandas\\core\\generic.py\u001b[0m in \u001b[0;36m__getattr__\u001b[1;34m(self, name)\u001b[0m\n\u001b[0;32m   5463\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_info_axis\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_can_hold_identifiers_and_holds_name\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   5464\u001b[0m                 \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 5465\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   5466\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   5467\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAttributeError\u001b[0m: 'Series' object has no attribute 'pie'"
     ]
    }
   ],
   "source": [
    "# https://blog.csdn.net/qq_41081716/article/details/103128866\n",
    "# plt.plot(data[\"所在市\"])\n",
    "data[\"所在市\"].pie()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a73c5e32",
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "could not convert string to float: '舟山市'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-13-a19455bfa663>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpie\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"所在市\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[1;31m# https://blog.csdn.net/weixin_39867893/article/details/110971498\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\project\\python_project\\albert\\venv\\lib\\site-packages\\matplotlib\\pyplot.py\u001b[0m in \u001b[0;36mpie\u001b[1;34m(x, explode, labels, colors, autopct, pctdistance, shadow, labeldistance, startangle, radius, counterclock, wedgeprops, textprops, center, frame, rotatelabels, normalize, data)\u001b[0m\n\u001b[0;32m   2980\u001b[0m         \u001b[0mwedgeprops\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mwedgeprops\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtextprops\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mtextprops\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcenter\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcenter\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2981\u001b[0m         \u001b[0mframe\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mframe\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrotatelabels\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mrotatelabels\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnormalize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mnormalize\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2982\u001b[1;33m         **({\"data\": data} if data is not None else {}))\n\u001b[0m\u001b[0;32m   2983\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2984\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\project\\python_project\\albert\\venv\\lib\\site-packages\\matplotlib\\__init__.py\u001b[0m in \u001b[0;36minner\u001b[1;34m(ax, data, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1350\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0minner\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1351\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mdata\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1352\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0mmap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msanitize_sequence\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1353\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1354\u001b[0m         \u001b[0mbound\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnew_sig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbind\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\project\\python_project\\albert\\venv\\lib\\site-packages\\matplotlib\\axes\\_axes.py\u001b[0m in \u001b[0;36mpie\u001b[1;34m(self, x, explode, labels, colors, autopct, pctdistance, shadow, labeldistance, startangle, radius, counterclock, wedgeprops, textprops, center, frame, rotatelabels, normalize)\u001b[0m\n\u001b[0;32m   3027\u001b[0m         \u001b[1;31m# The use of float32 is \"historical\", but can't be changed without\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3028\u001b[0m         \u001b[1;31m# regenerating the test baselines.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3029\u001b[1;33m         \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfloat32\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3030\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[1;33m>\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3031\u001b[0m             \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"x must be 1D\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\project\\python_project\\albert\\venv\\lib\\site-packages\\numpy\\core\\_asarray.py\u001b[0m in \u001b[0;36masarray\u001b[1;34m(a, dtype, order)\u001b[0m\n\u001b[0;32m     81\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     82\u001b[0m     \"\"\"\n\u001b[1;32m---> 83\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0marray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0morder\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0morder\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     84\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     85\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: could not convert string to float: '舟山市'"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pie(list(data[\"所在市\"]))\n",
    "# x 要写的是数量，labels=才是舟山市那些\n",
    "# https://blog.csdn.net/weixin_39867893/article/details/110971498"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7973d154",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['舟山市',\n",
       " '杭州市',\n",
       " '杭州市',\n",
       " '杭州市',\n",
       " '绍兴市',\n",
       " '宁波市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '杭州市',\n",
       " '杭州市',\n",
       " '杭州市',\n",
       " '杭州市',\n",
       " '舟山市',\n",
       " '嘉兴市',\n",
       " '嘉兴市',\n",
       " '杭州市',\n",
       " '舟山市',\n",
       " '杭州市',\n",
       " '杭州市',\n",
       " '金华市',\n",
       " '湖州市',\n",
       " '杭州市',\n",
       " '嘉兴市',\n",
       " '杭州市',\n",
       " '嘉兴市',\n",
       " '杭州市',\n",
       " '金华市',\n",
       " '杭州市',\n",
       " '湖州市',\n",
       " '舟山市',\n",
       " '杭州市',\n",
       " '杭州市',\n",
       " '宁波市',\n",
       " '金华市',\n",
       " '丽水市',\n",
       " '杭州市',\n",
       " '金华市',\n",
       " '杭州市',\n",
       " '宁波市',\n",
       " '绍兴市',\n",
       " '丽水市',\n",
       " '衢州市',\n",
       " '绍兴市',\n",
       " '金华市',\n",
       " '衢州市',\n",
       " '舟山市',\n",
       " '宁波市',\n",
       " '杭州市',\n",
       " '宁波市',\n",
       " '温州市',\n",
       " '绍兴市',\n",
       " '杭州市',\n",
       " '杭州市',\n",
       " '台州市',\n",
       " '杭州市',\n",
       " '杭州市',\n",
       " '杭州市',\n",
       " '杭州市',\n",
       " '丽水市',\n",
       " '绍兴市',\n",
       " '温州市',\n",
       " '宁波市',\n",
       " '金华市',\n",
       " '杭州市',\n",
       " '杭州市',\n",
       " '金华市',\n",
       " '杭州市',\n",
       " '嘉兴市',\n",
       " '杭州市',\n",
       " '衢州市',\n",
       " '温州市',\n",
       " '杭州市',\n",
       " '衢州市',\n",
       " '杭州市',\n",
       " '宁波市',\n",
       " '金华市',\n",
       " '杭州市',\n",
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       " '温州市',\n",
       " '宁波市',\n",
       " '台州市',\n",
       " '嘉兴市',\n",
       " '绍兴市',\n",
       " '宁波市',\n",
       " '嘉兴市',\n",
       " '台州市',\n",
       " '绍兴市',\n",
       " '台州市',\n",
       " '金华市',\n",
       " '衢州市',\n",
       " '金华市',\n",
       " '绍兴市',\n",
       " '台州市',\n",
       " '嘉兴市',\n",
       " '湖州市',\n",
       " '温州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '绍兴市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '绍兴市',\n",
       " '绍兴市',\n",
       " '衢州市',\n",
       " '绍兴市',\n",
       " '衢州市',\n",
       " '绍兴市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '宁波市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '金华市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '绍兴市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '绍兴市',\n",
       " '绍兴市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '温州市',\n",
       " '宁波市',\n",
       " '绍兴市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '衢州市',\n",
       " '绍兴市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '温州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '温州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '杭州市',\n",
       " '宁波市',\n",
       " '杭州市',\n",
       " '台州市',\n",
       " '杭州市',\n",
       " '杭州市',\n",
       " '宁波市',\n",
       " '湖州市',\n",
       " '杭州市',\n",
       " '温州市',\n",
       " '杭州市',\n",
       " '湖州市',\n",
       " '绍兴市',\n",
       " '温州市',\n",
       " '嘉兴市',\n",
       " '宁波市',\n",
       " '温州市',\n",
       " '衢州市',\n",
       " '温州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '温州市',\n",
       " '台州市',\n",
       " '宁波市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '宁波市',\n",
       " '衢州市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '金华市',\n",
       " '宁波市',\n",
       " '绍兴市',\n",
       " '宁波市',\n",
       " '绍兴市',\n",
       " '宁波市',\n",
       " '衢州市',\n",
       " '宁波市',\n",
       " '衢州市',\n",
       " '台州市',\n",
       " '台州市',\n",
       " '嘉兴市',\n",
       " '温州市',\n",
       " '杭州市',\n",
       " '温州市',\n",
       " '嘉兴市',\n",
       " '温州市',\n",
       " '杭州市',\n",
       " '衢州市',\n",
       " '温州市',\n",
       " '杭州市',\n",
       " '宁波市',\n",
       " '温州市',\n",
       " '温州市',\n",
       " '衢州市',\n",
       " '杭州市',\n",
       " '宁波市',\n",
       " '衢州市',\n",
       " '温州市',\n",
       " '台州市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '温州市',\n",
       " '杭州市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '温州市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '温州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '温州市',\n",
       " '温州市',\n",
       " '杭州市',\n",
       " '衢州市',\n",
       " '宁波市',\n",
       " '温州市',\n",
       " '温州市',\n",
       " '金华市',\n",
       " '衢州市',\n",
       " '宁波市',\n",
       " '温州市',\n",
       " '衢州市',\n",
       " '宁波市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '嘉兴市',\n",
       " '衢州市',\n",
       " '宁波市',\n",
       " '温州市',\n",
       " '杭州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '宁波市',\n",
       " '衢州市',\n",
       " '嘉兴市',\n",
       " '宁波市',\n",
       " '温州市',\n",
       " '杭州市',\n",
       " '衢州市',\n",
       " '衢州市',\n",
       " '台州市',\n",
       " '杭州市',\n",
       " '舟山市',\n",
       " '宁波市',\n",
       " '丽水市',\n",
       " '杭州市',\n",
       " '杭州市',\n",
       " '杭州市',\n",
       " '温州市',\n",
       " '宁波市',\n",
       " '宁波市',\n",
       " '杭州市',\n",
       " '丽水市',\n",
       " '湖州市',\n",
       " '杭州市',\n",
       " '衢州市',\n",
       " '台州市',\n",
       " '嘉兴市',\n",
       " '温州市',\n",
       " '丽水市',\n",
       " '温州市',\n",
       " '宁波市',\n",
       " '丽水市',\n",
       " '台州市',\n",
       " '衢州市',\n",
       " '湖州市',\n",
       " '台州市',\n",
       " '杭州市',\n",
       " '湖州市',\n",
       " '台州市',\n",
       " '宁波市',\n",
       " '衢州市',\n",
       " '丽水市',\n",
       " '衢州市',\n",
       " '嘉兴市',\n",
       " '衢州市',\n",
       " '绍兴市',\n",
       " '衢州市',\n",
       " '宁波市',\n",
       " '湖州市',\n",
       " '温州市',\n",
       " '宁波市',\n",
       " '舟山市',\n",
       " '杭州市',\n",
       " '嘉兴市',\n",
       " '绍兴市',\n",
       " '宁波市',\n",
       " '温州市',\n",
       " '衢州市',\n",
       " '丽水市',\n",
       " '温州市',\n",
       " '衢州市',\n",
       " '宁波市',\n",
       " '杭州市',\n",
       " '丽水市',\n",
       " '湖州市',\n",
       " '台州市',\n",
       " '金华市',\n",
       " '丽水市',\n",
       " '宁波市',\n",
       " '丽水市',\n",
       " '丽水市',\n",
       " '丽水市',\n",
       " '丽水市',\n",
       " '温州市',\n",
       " '温州市',\n",
       " '宁波市',\n",
       " '丽水市',\n",
       " '嘉兴市',\n",
       " '金华市',\n",
       " '舟山市',\n",
       " '温州市',\n",
       " '衢州市',\n",
       " '湖州市',\n",
       " '衢州市',\n",
       " '金华市',\n",
       " '温州市',\n",
       " '丽水市',\n",
       " '丽水市',\n",
       " '温州市',\n",
       " '宁波市',\n",
       " '丽水市',\n",
       " '杭州市',\n",
       " '衢州市',\n",
       " '温州市',\n",
       " '宁波市',\n",
       " '台州市',\n",
       " '衢州市',\n",
       " '宁波市',\n",
       " '舟山市',\n",
       " '丽水市',\n",
       " '温州市',\n",
       " '湖州市',\n",
       " '绍兴市',\n",
       " '嘉兴市',\n",
       " ...]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(data[\"所在市\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "09ebb63c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       舟山市\n",
       "1       杭州市\n",
       "2       杭州市\n",
       "3       杭州市\n",
       "4       绍兴市\n",
       "       ... \n",
       "4995    衢州市\n",
       "4996    湖州市\n",
       "4997    嘉兴市\n",
       "4998    衢州市\n",
       "4999    衢州市\n",
       "Name: 所在市, Length: 5000, dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"所在市\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "cb4a58c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.patches.Wedge at 0x193fd647548>,\n",
       "  <matplotlib.patches.Wedge at 0x193fd64e548>,\n",
       "  <matplotlib.patches.Wedge at 0x193fd64ed88>,\n",
       "  <matplotlib.patches.Wedge at 0x193fd653748>,\n",
       "  <matplotlib.patches.Wedge at 0x193fd65b248>],\n",
       " [Text(1.075962358309037, 0.22870287165240302, ''),\n",
       "  Text(0.7360436312779136, 0.817459340184711, ''),\n",
       "  Text(-0.33991877217145816, 1.046162142464278, ''),\n",
       "  Text(-1.0759623315431446, -0.2287029975759841, ''),\n",
       "  Text(0.5500001932481627, -0.9526278325909777, '')])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pie([1,2,3,4,5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "61644167",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "舟山市\n",
      "杭州市\n",
      "杭州市\n",
      "杭州市\n",
      "绍兴市\n",
      "宁波市\n",
      "衢州市\n",
      "衢州市\n",
      "杭州市\n",
      "杭州市\n",
      "杭州市\n",
      "杭州市\n",
      "舟山市\n",
      "嘉兴市\n",
      "嘉兴市\n",
      "杭州市\n",
      "舟山市\n",
      "杭州市\n",
      "杭州市\n",
      "金华市\n",
      "湖州市\n",
      "杭州市\n",
      "嘉兴市\n",
      "杭州市\n",
      "嘉兴市\n",
      "杭州市\n",
      "金华市\n",
      "杭州市\n",
      "湖州市\n",
      "舟山市\n",
      "杭州市\n",
      "杭州市\n",
      "宁波市\n",
      "金华市\n",
      "丽水市\n",
      "杭州市\n",
      "金华市\n",
      "杭州市\n",
      "宁波市\n",
      "绍兴市\n",
      "丽水市\n",
      "衢州市\n",
      "绍兴市\n",
      "金华市\n",
      "衢州市\n",
      "舟山市\n",
      "宁波市\n",
      "杭州市\n",
      "宁波市\n",
      "温州市\n",
      "绍兴市\n",
      "杭州市\n",
      "杭州市\n",
      "台州市\n",
      "杭州市\n",
      "杭州市\n",
      "杭州市\n",
      "杭州市\n",
      "丽水市\n",
      "绍兴市\n",
      "温州市\n",
      "宁波市\n",
      "金华市\n",
      "杭州市\n",
      "杭州市\n",
      "金华市\n",
      "杭州市\n",
      "嘉兴市\n",
      "杭州市\n",
      "衢州市\n",
      "温州市\n",
      "杭州市\n",
      "衢州市\n",
      "杭州市\n",
      "宁波市\n",
      "金华市\n",
      "杭州市\n",
      "温州市\n",
      "金华市\n",
      "绍兴市\n",
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      "宁波市\n",
      "宁波市\n",
      "宁波市\n",
      "宁波市\n",
      "宁波市\n",
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      "绍兴市\n",
      "宁波市\n",
      "宁波市\n",
      "宁波市\n",
      "宁波市\n",
      "宁波市\n",
      "宁波市\n",
      "宁波市\n",
      "宁波市\n",
      "宁波市\n",
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      "衢州市\n",
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      "衢州市\n",
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      "宁波市\n",
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      "衢州市\n",
      "衢州市\n",
      "衢州市\n",
      "宁波市\n",
      "宁波市\n",
      "杭州市\n",
      "宁波市\n",
      "杭州市\n",
      "台州市\n",
      "杭州市\n",
      "杭州市\n",
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      "湖州市\n",
      "杭州市\n",
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      "杭州市\n",
      "湖州市\n",
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      "温州市\n",
      "衢州市\n",
      "衢州市\n",
      "温州市\n",
      "台州市\n",
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      "衢州市\n",
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      "宁波市\n",
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      "宁波市\n",
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      "宁波市\n",
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      "衢州市\n",
      "金华市\n",
      "温州市\n",
      "湖州市\n",
      "湖州市\n",
      "丽水市\n",
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      "宁波市\n",
      "湖州市\n",
      "绍兴市\n",
      "舟山市\n",
      "绍兴市\n",
      "金华市\n",
      "绍兴市\n",
      "杭州市\n",
      "嘉兴市\n",
      "舟山市\n",
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      "杭州市\n",
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      "宁波市\n",
      "衢州市\n",
      "台州市\n",
      "丽水市\n",
      "丽水市\n",
      "绍兴市\n",
      "舟山市\n",
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      "衢州市\n",
      "杭州市\n",
      "杭州市\n",
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      "舟山市\n",
      "宁波市\n",
      "丽水市\n",
      "丽水市\n",
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      "杭州市\n",
      "台州市\n",
      "金华市\n",
      "丽水市\n",
      "湖州市\n",
      "衢州市\n",
      "丽水市\n",
      "温州市\n",
      "嘉兴市\n",
      "金华市\n",
      "嘉兴市\n",
      "嘉兴市\n",
      "衢州市\n",
      "金华市\n",
      "衢州市\n",
      "温州市\n",
      "丽水市\n",
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      "金华市\n",
      "温州市\n",
      "宁波市\n",
      "温州市\n",
      "宁波市\n",
      "绍兴市\n",
      "杭州市\n",
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      "金华市\n",
      "金华市\n",
      "金华市\n",
      "湖州市\n",
      "金华市\n",
      "衢州市\n",
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      "丽水市\n",
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      "宁波市\n",
      "金华市\n",
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      "金华市\n",
      "湖州市\n",
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      "湖州市\n",
      "宁波市\n",
      "湖州市\n",
      "丽水市\n",
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      "衢州市\n",
      "丽水市\n",
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      "嘉兴市\n",
      "台州市\n",
      "杭州市\n",
      "衢州市\n",
      "丽水市\n",
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      "丽水市\n",
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      "宁波市\n",
      "金华市\n",
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      "湖州市\n",
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      "嘉兴市\n",
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      "嘉兴市\n",
      "温州市\n",
      "嘉兴市\n",
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      "湖州市\n",
      "绍兴市\n",
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      "台州市\n",
      "湖州市\n",
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      "宁波市\n",
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      "丽水市\n",
      "湖州市\n",
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      "台州市\n",
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      "嘉兴市\n",
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      "衢州市\n",
      "舟山市\n",
      "舟山市\n",
      "台州市\n",
      "嘉兴市\n",
      "绍兴市\n",
      "金华市\n",
      "温州市\n",
      "温州市\n",
      "丽水市\n",
      "台州市\n",
      "嘉兴市\n",
      "衢州市\n",
      "金华市\n",
      "衢州市\n",
      "衢州市\n",
      "嘉兴市\n",
      "温州市\n",
      "绍兴市\n",
      "绍兴市\n",
      "嘉兴市\n",
      "金华市\n",
      "温州市\n",
      "衢州市\n",
      "台州市\n",
      "温州市\n",
      "衢州市\n",
      "绍兴市\n",
      "衢州市\n",
      "绍兴市\n",
      "绍兴市\n",
      "衢州市\n",
      "金华市\n",
      "金华市\n",
      "台州市\n",
      "衢州市\n",
      "舟山市\n",
      "金华市\n",
      "金华市\n",
      "台州市\n",
      "金华市\n",
      "绍兴市\n",
      "绍兴市\n",
      "金华市\n",
      "湖州市\n",
      "宁波市\n",
      "宁波市\n",
      "嘉兴市\n",
      "衢州市\n",
      "宁波市\n",
      "嘉兴市\n",
      "绍兴市\n",
      "宁波市\n",
      "台州市\n",
      "衢州市\n",
      "衢州市\n",
      "嘉兴市\n",
      "宁波市\n",
      "衢州市\n",
      "金华市\n",
      "嘉兴市\n",
      "金华市\n",
      "衢州市\n",
      "衢州市\n",
      "嘉兴市\n",
      "宁波市\n",
      "台州市\n",
      "金华市\n",
      "衢州市\n",
      "衢州市\n",
      "嘉兴市\n",
      "宁波市\n",
      "宁波市\n",
      "衢州市\n",
      "湖州市\n",
      "宁波市\n",
      "杭州市\n",
      "衢州市\n",
      "衢州市\n",
      "温州市\n",
      "宁波市\n",
      "衢州市\n",
      "宁波市\n",
      "嘉兴市\n",
      "绍兴市\n",
      "衢州市\n",
      "衢州市\n",
      "金华市\n",
      "绍兴市\n",
      "宁波市\n",
      "温州市\n",
      "嘉兴市\n",
      "台州市\n",
      "宁波市\n",
      "衢州市\n",
      "衢州市\n",
      "金华市\n",
      "杭州市\n",
      "衢州市\n",
      "衢州市\n",
      "衢州市\n",
      "嘉兴市\n",
      "湖州市\n",
      "绍兴市\n",
      "嘉兴市\n",
      "嘉兴市\n",
      "温州市\n",
      "舟山市\n",
      "丽水市\n",
      "温州市\n",
      "金华市\n",
      "湖州市\n",
      "衢州市\n",
      "宁波市\n",
      "绍兴市\n",
      "杭州市\n",
      "台州市\n",
      "金华市\n",
      "衢州市\n",
      "舟山市\n",
      "舟山市\n",
      "温州市\n",
      "宁波市\n",
      "衢州市\n",
      "湖州市\n",
      "嘉兴市\n",
      "衢州市\n",
      "衢州市\n"
     ]
    }
   ],
   "source": [
    "# https://blog.csdn.net/weixin_43189702/article/details/103513141\n",
    "for shi in data[\"所在市\"]:\n",
    "    print(shi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2d404020",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'丽水市', '台州市', '嘉兴市', '宁波市', '杭州市', '温州市', '湖州市', '绍兴市', '舟山市', '衢州市', '金华市'}"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set(data[\"所在市\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "e6161f54",
   "metadata": {},
   "outputs": [],
   "source": [
    "city_names=list(set(data[\"所在市\"]))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "579b3504",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "嘉兴市\n",
      "温州市\n",
      "丽水市\n",
      "舟山市\n",
      "衢州市\n",
      "宁波市\n",
      "金华市\n",
      "湖州市\n",
      "杭州市\n",
      "台州市\n",
      "绍兴市\n"
     ]
    }
   ],
   "source": [
    "for city in city_names:\n",
    "    print(city)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "da6f2d13",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.patches.Wedge at 0x193fd6c6a08>,\n",
       "  <matplotlib.patches.Wedge at 0x193fd6db2c8>,\n",
       "  <matplotlib.patches.Wedge at 0x193fd6db988>,\n",
       "  <matplotlib.patches.Wedge at 0x193fd6e5048>,\n",
       "  <matplotlib.patches.Wedge at 0x193fd6e5708>,\n",
       "  <matplotlib.patches.Wedge at 0x193fd6e5ec8>,\n",
       "  <matplotlib.patches.Wedge at 0x193fd6ed648>,\n",
       "  <matplotlib.patches.Wedge at 0x193fd6edd08>,\n",
       "  <matplotlib.patches.Wedge at 0x193fd6e5748>,\n",
       "  <matplotlib.patches.Wedge at 0x193fd6e5f08>,\n",
       "  <matplotlib.patches.Wedge at 0x193fd671948>],\n",
       " [Text(1.078525385021709, 0.21629376751024243, '嘉兴市'),\n",
       "  Text(0.893963583036798, 0.6409595246222729, '温州市'),\n",
       "  Text(0.47460166474305626, 0.9923473483730986, '丽水市'),\n",
       "  Text(0.009676002770810847, 1.0999574423451026, '舟山市'),\n",
       "  Text(-0.48455363782411937, 0.9875260867801987, '衢州市'),\n",
       "  Text(-0.9887407581160057, 0.48207023683296035, '宁波市'),\n",
       "  Text(-1.0280079854497035, -0.39140718165567984, '金华市'),\n",
       "  Text(-0.5189935612217298, -0.9698689001150551, '湖州市'),\n",
       "  Text(0.19796671188681053, -1.0820393620311253, '杭州市'),\n",
       "  Text(0.8214552029809027, -0.7315814031914726, '台州市'),\n",
       "  Text(1.0681376966953329, -0.2628342841000568, '绍兴市')])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fracs=[]\n",
    "city_col=data[\"所在市\"]\n",
    "for city in city_names:\n",
    "    fracs.append(city_col[city_col==city].shape[0])\n",
    "plt.pie(fracs,labels=city_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "1d3219e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def pie_list(lst_data):\n",
    "    labels=list(set(lst_data))\n",
    "    fracs=[]\n",
    "#     city_col=data[\"所在市\"]\n",
    "    for label in labels:\n",
    "        fracs.append(lst_data[lst_data==label].shape[0])\n",
    "    plt.pie(fracs,labels=labels)\n",
    "    \n",
    "pie_list(data[\"所在市\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "05cc1082",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pie_list(data[\"完成情况\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "6d043715",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x193fd8a7448>]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(data[\"完成情况\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "346026ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x193fff22e08>]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(list(data[\"完成情况\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "ed426ffa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_list(lst_data):\n",
    "    labels=list(set(lst_data))\n",
    "    fracs=[]\n",
    "#     city_col=data[\"所在市\"]\n",
    "    for label in labels:\n",
    "        fracs.append(lst_data[lst_data==label].shape[0])\n",
    "#     plt.plot(fracs,labels)\n",
    "    plt.plot(labels,fracs)\n",
    "    \n",
    "plot_list(data[\"完成情况\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "5012f796",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "def get_fracs_and_labels(lst_data):\n",
    "    labels=list(set(lst_data))\n",
    "    fracs=[]\n",
    "    #     city_col=data[\"所在市\"]\n",
    "    for label in labels:\n",
    "        fracs.append(lst_data[lst_data==label].shape[0])\n",
    "    return fracs,labels\n",
    "\n",
    "def bar_list(lst_data):\n",
    "    fracs,labels=get_fracs_and_labels(lst_data)\n",
    "    plt.bar(x=labels,height=fracs)\n",
    "\n",
    "# https://blog.csdn.net/qq_37532736/article/details/89486207\n",
    "bar_list(data[\"完成情况\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b2cdad3b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
